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Short-term load prediction method and device based on deep neural network

A deep neural network, short-term load forecasting technology, applied in biological neural network models, forecasting, neural architecture, etc., can solve the problems of machine learning algorithm training not meeting the requirements, inaccurate forecast results, etc., to reduce the computational workload, The effect of reducing the amount of training data and improving the quality

Pending Publication Date: 2019-09-10
POWER DISPATCHING CONTROL CENT OF GUANGDONG POWER GRID CO LTD
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AI Technical Summary

Problems solved by technology

However, the current short-term load forecasting method based on DNN is not up to the requirements of machine learning algorithm training, resulting in inaccurate forecasting results

Method used

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  • Short-term load prediction method and device based on deep neural network
  • Short-term load prediction method and device based on deep neural network
  • Short-term load prediction method and device based on deep neural network

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Embodiment Construction

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0035] Please refer to figure 1 It shows a short-term load forecasting method based on a deep neural network provided by an exemplary embodiment of the present invention, the steps include:

[0036] S101. Obtain historical data and feature data to be predicted; wherein, the historical data includes detected load values, historical forecast load values, historical short-term load forecast accuracy values, etc.; the feature data includes the data obtained before this...

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Abstract

The invention discloses a short-term load prediction method based on a deep neural network. The method comprises the steps of obtaining the historical data and the feature data to be predicted; calculating the similarity measurement of the historical data and the feature data; selecting a plurality of data samples from the historical data according to the similarity measurement, and endowing eachdata sample with a training weight to obtain a sample training set; using the sample training set to train a deep neural network model to obtain a prediction model, wherein the feature data is calculated through the prediction model to obtain a prediction result. According to the method, the samples are screened and different training weights are given to the samples, so that the prediction modelbased on the deep neural network can learn the training samples in a targeted manner, and the accuracy and the precision of the short-term load prediction are improved.

Description

technical field [0001] The invention relates to the technical field of power load forecasting, in particular to a short-term load forecasting method and device based on a deep neural network. Background technique [0002] Short-term load forecasting is the basis for the safe and economical operation of the power system. With the continuous improvement of my country's power market system, the role of short-term load forecasting is becoming increasingly important. At present, experts and scholars at home and abroad have carried out a lot of research on short-term load forecasting, and proposed a series of intelligent forecasting methods based on machine learning. Among them, Deep Neural Network (DNN) is one of the most commonly used machine learning algorithms. However, the current short-term load forecasting method based on DNN is inaccurate because the training of the machine learning algorithm is not up to the requirements. Contents of the invention [0003] In view of t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06Q10/04G06Q50/06H02J3/00
CPCG06Q10/04G06Q50/06H02J3/00H02J3/003H02J2203/20G06N3/045G06F18/22G06F18/214
Inventor 蔡秋娜左剑张乔榆闫斌杰苏炳洪刘思捷
Owner POWER DISPATCHING CONTROL CENT OF GUANGDONG POWER GRID CO LTD